Cooperative mobile edge computing system for VANET-based software-defined content delivery

Albadarneh, Jafar; Jararweh, Yaser; Al‐Ayyoub, Mahmoud; Fontes, Ramon dos Reis; Al-Smadi, Mohammad; Rothenberg, Christian Esteve

doi:10.1016/j.compeleceng.2018.07.021

Cited by 34 publications

(16 citation statements)

References 12 publications

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“…In [20], an MEC layer was proposed to process information coming from vehicles implementing a vehicular social network, although the potential of NFV and MANO was not exploited to cope with the dynamism of the system. The same lack is found in [21], in which a content delivery network used a MEC-based architecture to speed-up data sharing among vehicles.…”

Section: Related Workmentioning

confidence: 78%

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

et al. 2019

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Virtualization technologies are key enablers of softwarized 5G networks, and their usage in the vehicular domain can provide flexibility and reliability in real deployments, where mobility and processing needs may be an issue. Next-generation vehicular services, such as the ones in the area of urban mobility and, in general, those interconnecting on-board sensors, require continuous data gathering and processing, but current architectures are stratified in two-tier solutions in which data is collected by on-board units (OBU) and sent to cloud servers. In this line, intermediate cache and processing layers are needed in order to cover quasi-ubiquitous data-gathering needs of vehicles in scenarios of smart cities/roads considering vehicles as moving sensors. The SURROGATES solution presented in this paper proposes to virtualize vehicle OBUs and create a novel Multi-Access Edge Computing (MEC) layer with the aim of offloading processing from the vehicle and serving data-access requests. This deals with potential disconnection periods of vehicles, saves radio resources when accessing the physical OBU and improves data processing performance. A proof of concept has been implemented using OpenStack and Open Source MANO to virtualize resources and gather data from in-vehicle sensors, and a final traffic monitoring service has been implemented to validate the proposal. Performance results reveal a speedup of more than 50% in the data request resolution, with consequently great savings of network resources in the wireless segment. Thus, this work opens a novel path regarding the virtualization of end-devices in the Intelligent Transportation Systems (ITS) ecosystem.

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Section: Related Workmentioning

confidence: 78%

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

et al. 2019

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“…In [9], a latency performance evaluation was discussed for processing latency sensitive services using the construction model of the software-defined cloud/fog network graph model. Furthermore, edge computing approach for delivering traffic content query requested by vehicles was proposed in [45]. The approach in [45] enabled vehicles to communicate with neighboring ones through vehicle-level caching technique to minimize the network latency.…”

Section: Sdn Controller Assistance For Vm Migration Over Sdvcmentioning

confidence: 99%

“…Furthermore, edge computing approach for delivering traffic content query requested by vehicles was proposed in [45]. The approach in [45] enabled vehicles to communicate with neighboring ones through vehicle-level caching technique to minimize the network latency. Automation of traffic, improvement on disseminating driver and pedestrian safety messages, and monitoring of traffic violations are implemented through an intelligent transport system based on MEC and SDN technologies [46].…”

Section: Sdn Controller Assistance For Vm Migration Over Sdvcmentioning

confidence: 99%

“…Mininet-WiFi is an extension of the Mininet [59] emulator to simulate a mobile wireless node. SUMO is used to inject traffic mobility to allow Mininet-WiFi to evaluate SDVN architecture [45,52]. However, the Mininet-WiFi platform lacks the ability to apply VM migration technologies.…”

Section: Simulation Tools For Vm Migration Services Over Sdvcmentioning

confidence: 99%

“…Table 2 shows that most SD-based vehicular and edge cloud computing concentrates on mathematical analysis rather than to realistic simulation environments. A vehicular edge/fog computing to support the control layer over SDVN for content delivery is discussed in [9,[45][46][47][48]. Al-Badarneh et al [45] and Campolo et al [52] evaluated slicing road framework in 5G network softwarization for content delivery using Mininet-WiFi emulator.…”

Section: Simulation Tools For Vm Migration Services Over Sdvcmentioning

confidence: 99%

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Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration

Nkenyereye

Tama

et al. 2020

Sensors

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Cloud computing supports many unprecedented cloud-based vehicular applications. To improve connectivity and bandwidth through programmable networking architectures, Software- Defined (SD) Vehicular Network (SDVN) is introduced. SDVN architecture enables vehicles to be equipped with SDN OpenFlow switch on which the routing rules are updated from a SDN OpenFlow controller. From SDVN, new vehicular architectures are introduced, for instance SD Vehicular Cloud (SDVC). In SDVC, vehicles are SDN devices that host virtualization technology for enabling deployment of cloud-based vehicular applications. In addition, the migration of Virtual Machines (VM) over SDVC challenges the performance of cloud-based vehicular applications due the highly mobility of vehicles. However, the current literature that discusses VM migration in SDVC is very limited. In this paper, we first analyze the evolution of computation and networking technologies of SDVC with a focus on its architecture within the cloud-based vehicular environment. Then, we discuss the potential cloud-based vehicular applications assisted by the SDVC along with its ability to manage several VM migration scenarios. Lastly, we provide a detailed comparison of existing frameworks in SDVC that integrate the VM migration approach and different emulators or simulators network used to evaluate VM frameworks’ use cases.

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Software defined vehicular networks: A comprehensive review

Bhatia

Modi

Tanwar

et al. 2019

Int J Communication

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SummaryThe recent breakthroughs in the automobile industries and telecommunication technologies along with the exceptional multimodal mobility services brought focus on intelligent transportation system (ITS), of which vehicular ad hoc networks (VANETs) gain much more attention. The distinctive features of software‐defined networking (SDN) leverages the vehicular networks by its state of the centralized art having a comprehensive view of the network. Its potential to bring the flexibility, programmability and other extensive advancements to vehicular networks has set the stage for a novel networking paradigm termed as software‐defined vehicular networks (SDVNs). Many researchers have demonstrated the SDN‐based VANETs with the various configuration of the SDN components in VANET architecture. However, a compilation of the work on the SDN‐based VANET system as a whole, incorporating its architecture, use‐cases, and opportunities, is still inadequate. We start with the summary of the recent studies that exist on the SDVNs, followed by the comprehensive explanation of its components. Next, we present the taxonomy of SDVN based on the architecture modes, protocols, access technologies, and opportunities with trending technologies. Finally, we highlight the challenges, open research issues, and future research directions.

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Cooperative mobile edge computing system for VANET-based software-defined content delivery

Cited by 34 publications

References 12 publications

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

Software-Defined Vehicular Cloud Networks: Architecture, Applications and Virtual Machine Migration

Software defined vehicular networks: A comprehensive review

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